System and methods for measuring propulsive force during ambulation and providing real-time feedback

ABSTRACT

The invention measures propulsive force of an ambulating subject to provide real-time feedback, which may be used for clinical assessment or rehabilitation/training such as that related to walking ability, or any other form of ambulation. Subjects with propulsive deficits have a considerable and underutilized propulsive reserve available during level ambulation. The invention uses real-time propulsive feedback as a therapeutic strategy to encourage a subject to access the propulsive reserve and improve forward propulsion during ambulation.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. provisional application 61/820,743 filed May 8, 2013, which is incorporated by reference herein in its entirety.

FIELD OF THE INVENTION

The invention relates generally to measuring and using propulsive forces in rehabilitation or gait training. More specifically, the invention comprises a system and methods that provide real-time output, or feedback, of the propulsive force resultant from an ambulating subject. The feedback may be used for clinical assessment and/or rehabilitation such as that related to ambulation.

BACKGROUND OF THE INVENTION

Reduced propulsive function during the push-off phase when ambulating plays a central role in the deterioration of ambulation ability. For example, an injured person may have difficulty walking at the same speed as before the injury. Specifically, a patient may have difficulty walking after stroke, amputation, or joint replacement. A disabled person may always walk more slowly than others of the same physical strength. Also, an elderly person may walk at a slow speed due to age or fatigue. Furthermore, all of these subjects may have even greater difficulty walking or running uphill.

Compromised ambulation ability ultimately predicts health and survival. For example, among older adults, compromised walking ability is ultimately predictive of health problems and reduced survival. The prevalence of walking ability limitations among old adults is profound: 17%, 28% and 47% of people aged 65-74, 75-84, and 85+ years, respectively, report that walking difficulties interfere with their daily activities.

Considerable research has demonstrated that a reduction in propulsion during the push-off phase of walking, even in otherwise healthy old adults, plays a central role in the deterioration of walking ability with age. Specifically, old adults exert smaller peak propulsive force, perform less trailing leg positive mechanical work, and generate less ankle power than young adults walking at the same speed. Eventually, the propulsive deficits of old adults may lead to slower walking speeds on the level, inability to walk uphill, and an associated loss of independence in the community. It is typically presumed that sarcopenia and leg muscle weakness are responsible for these changes. Such a presumption has understandably led to the widespread prescription of muscle strengthening programs for old adults.

While these programs improve muscle strength and mitigate sarcopenia, strengthening alone generally fails to improve the walking ability of old adults. Those outcomes suggest that factors other than sarcopenia bring the propulsive deficits of older adults. Furthermore, some metrics of propulsion such as ankle power generation, require complex calculations that are impractical to implement using real-time feedback.

There is a need for real-time feedback of propulsive forces to strategically tap into a subject's underutilized, but considerable, propulsive reserve during level ambulation to improve forward propulsion, which may be used in the development of more effective rehabilitative and prehabilitative therapies in order to improve ambulation in subjects. The invention satisfies this need.

SUMMARY OF THE INVENTION

For purposes of this application, the invention is discussed in reference to improving ambulatory activity of subjects that are human, but the discussion is merely exemplary. The invention is applicable to a wide range of subjects including animals. In addition, the term “ambulate” refers to any locomotion, such as walking, running, or even moving with crutches. Old subjects who exhibit diminished forward propulsion when ambulating over level ground at a comfortable speed can both voluntarily ambulate faster and ambulate uphill evidencing an underutilized propulsive reserve available during ambulation. As an example, compared to level walking, old subjects increase their peak propulsive ground reaction forces (GRFs), trailing leg positive mechanical work, and average ankle power generation during push-off by 69%, 115%, and 44% to walk uphill, respectively.

According to the invention, real-time propulsive feedback in the form of metrics related to ground reaction forces (GRFs) and ankle extensor (plantar flexor) muscle activities are used to exhibit that old subjects have an underutilized propulsive reserve. Old subjects can increase their peak propulsive GRFs and ankle extensor muscle activities during level ambulation. Real-time feedback elicits peak propulsive GRFs comparable to young adults. Forward propulsion during ambulation predictably decreases as people take progressively shorter steps at the same speed and, for many reasons, old subjects typically choose shorter steps. Thus, auditory cues such as those from a metronome may be used to encourage old subjects to take slower, longer steps than normal to increase forward propulsion.

In one embodiment, the invention is directed to a propulsion system for measuring propulsive forces and providing feedback in real-time to improve ambulation of a subject. The system includes an ambulation device such as a motorized treadmill, and a computer device. The ambulation device facilitates a subject ambulating. The ambulation device further comprises a force detection device and a muscle activity detection device. The force detection device measures ground reaction force data as the subject ambulates on the ambulation device. The activity detection device measures electromyographic signal data from one or more muscles, such as the soleus muscle or gastrocnemius muscle, as the subject ambulates on the ambulation device. A computer device receives and analyzes in real-time the ground reaction force data and the electromyographic signal data. The computer may analyze real-time the ground reaction forces data to calculate a propulsive peak or a propulsive impulse from an anterior-posterior ground reaction force or the electromyographic signal data to compute a mean push-off electromyographic signal. The computer device produces a feedback output displayed on the user interface. Feedback output may include, for example, a graphic illustration or an auditory cue of the ground reaction force data, the electromyographic signal data, or stride frequency. The feedback allows the subject to adjust its ambulation, for example, to take slower, longer steps, to utilize the propulsive reserve available to ultimately improve the forward propulsion of the subject.

Certain examples of the ambulation device include a treadmill, moving walkway or sidewalk. Certain examples of the force detection device include a force platform, one or more force transducers, a scale apparatus, or custom insoles of footwear. Certain examples of the activity detection device include a cuff with a sensor, an electrode equipped with an amplifier such as a differential amplifier, or a camera.

Feedback regarding the performance of a subject's activity may be communicated, for example through a user interface. For purposes of this application, an interface is any system or component by which a subject can receive visual, aural, or other sensory information including vibration or other tactile information. Examples of user interfaces include a television, a monitor, a screen, a touchscreen, a wearable visual user interface such as Google Glass™, and any other desktop, portable, or mobile device. It is also contemplated that the user interface may allow a subject to enter information about their health or their ambulatory activities. In other embodiments, information about the ambulatory activities may be obtained by a computer device or directly from an ambulation device.

According to the invention, real-time feedback of propulsive effort may supplant the distal to proximal redistribution of muscle recruitment, thereby enabling old subjects to increase their forward propulsion.

According to the invention, three different approaches to increase propulsion in old subjects are considered: force feedback, EMG feedback, and auditory stride frequency cueing.

One objective of certain embodiments of the invention is to measure the propulsive effort being made by a person that is ambulating and communicate that effort as real-time feedback in order to enhance the forward propulsion and thereby the ambulatory activity of the person.

Another objective of certain embodiments of the invention is to provide information regarding the propulsive effort being made by a person while ambulating in a form that is easy to understand and thereby permit the person to make real-time corrections and increase their forward propulsion.

An additional objective of the invention is to provide information to a person during ambulation such that the person can improve his or her strength, health, and independence.

One advantage of certain embodiments of the invention is that through the use of the ambulation propulsion system a person may improve their overall ambulation, including for example, walking or running speed.

Another advantage of certain embodiments of the invention is that through the use of the ambulation propulsion system a person may improve their uphill ambulation ability.

Another advantage of certain embodiments of the invention is that through the use of the system and methods, feedback regarding propulsive force or other aspect of ambulation provided to the user may result in improved speed while walking or running.

Another advantage of certain embodiments of the invention is that through the use of the system and methods, feedback regarding propulsion force or other aspect of ambulation provided to the subject may result in ambulation becoming easier, such that the person consumes less oxygen while walking.

The invention and its attributes and advantages will be further understood and appreciated with reference to the detailed description below of presently contemplated embodiments, taken in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The preferred embodiments of the invention will be described in conjunction with the appended drawings provided to illustrate and not to the limit the invention, where like designations denote like elements, and in which:

FIG. 1 is a block diagram of one embodiment of a propulsion system according to the invention.

FIG. 2 is a flow chart of one embodiment of a propulsion system method according to the invention.

FIG. 3 is a schematic of a subject and the propulsion system according to the invention.

FIG. 4 is a graph illustrating mean peak propulsive force according to one embodiment of the invention.

FIG. 5 is a graph illustrating push-off muscle activity according to one embodiment of the invention.

FIG. 6 is a graph illustrating mean stance phase ground reaction force (GRF) profiles according to one embodiment of the invention.

FIG. 7 is a graph illustrating mean stance phase medial gastrocnemius and soleus activity according to one embodiment of the invention.

FIG. 8 is a graph illustrating post-feedback retention according to one embodiment of the invention.

FIG. 9 illustrates an embodiment of a computer device according to the invention.

FIG. 10 illustrates an exemplary cloud computing system according to the invention.

DETAILED DESCRIPTION

One embodiment the invention is directed to a propulsion system 100 as shown in FIG. 1. The propulsion system 100 includes an ambulation device 102 and a computer device 150. The ambulation device 102 further comprises a force detection device 104 and an activity detection device 106. Although the invention is described below with respect to ambulation in the form of walking, any locomotion is envisioned such as running or even moving with crutches.

The ambulation device 102 is a device that facilitates a subject walking on, for example a motorized treadmill. The ambulation device 102 includes a force detection device 104 and an activity detection device 106. The force detection device 104 measures three-dimensional ground reaction force (GRFs) data as the subjects walks on the ambulation device 102.

One embodiment of a force detection device 104 is a force platform. The activity detection device 106 is a wearable device that measures electromyographic (EMG) signal data produced by muscles as the subject walks on the ambulation device.

One embodiment of an activity detection device 106 is an electrode equipped with a differential amplifier. The activity detection device 106 may be positioned on leg muscles of the subject such as the soleus (SOL) and medial gastrocnemius (MG).

A computer device 150 is operably linked with the ambulation device 102, for example, electronically (wired) or wirelessly (e.g., using Bluetooth, ZigBee, radio signal, Wireless USB, RFID, IR, Wi-Fi, local area networks, wide area networks, or other wireless systems known in the art).

Specifically, the computer device 150 receives the measurements of the GRF data and EMG signal data from the force detection device 104 and activity detection device 106, respectively. The computer device 150 receives the GRF data and EMG signal data in real-time and further analyzes the data real-time. One analysis of the data uses an algorithm to calculate the propulsive peak of the anterior-posterior GRF and/or the mean push-off EMG. It is also envisioned that the algorithm may be used to calculate a propulsive impulse of the anterior-posterior GRF.

The computer device produces a feedback output displayed on the user interface. Feedback output may include, for example, a graphic illustration or an auditory cue of the ground reaction force data, the electromyographic signal data, or stride frequency.

FIG. 2 illustrates the steps of a propulsion system method 170 according to the invention. The method is directed to measuring propulsive force and providing feedback real-time to improve ambulation of a subject. An ambulation device is provided at step 171 that facilitates a subject walking. At step 173 a force detection device is used to measure ground reaction force data as the subject walks on the ambulation device. At step 175, an activity detection device is utilized to measure electromyographic signal data from one or more muscles, such as the soleus muscle or the medial gastrocnemius muscle, as the subject walks on the ambulation device. The ground reaction force data and the electromyographic signal data are analyzed real-time at step 177. The data analysis at step 177 may include calculation a propulsive peak of an anterior-posterior ground reaction force or computing a mean push-off electromyographic signal. The real-time analysis provides a feedback output that is communicated such as through a display device or speakers to the subject at step 179. For example, the feedback output may be displayed as a graphic illustration or an auditory cue. The feedback output may include more ground reaction force data, the electromyographic signal data, and a stride frequency. The feedback output allows the subject to adjust its ambulation, for example, to take slower, longer steps, to utilize the propulsive reserve available to ultimately improve the forward propulsion of the subject.

FIG. 3 illustrates a schematic of a subject and the propulsion system 200 according to the invention. After preparing the skin with fine sandpaper and alcohol, single differential electrodes 206 with wireless preamplifiers are positioned over old subjects' right leg soleus and bilaterally over their medial gastrocnemius (MG), and sampled at 2000 Hz. Electrode positions and signal quality may be verified by visual inspecting the electromyographic (EMG) signals while a subject performs standing calf raises. A force platform 204 mounted under the right side of a custom dual-belt motorized treadmill 202 records the three-dimensional ground reaction forces (GRF) for each subject's right leg at 1000 Hz. To synchronize the data, the GRF signals are delayed to account for the 300 ms transmission delay inherent to the wireless single preamplifiers of the differential electrodes 206.

An algorithm is used to continuously process and monitor the GRF data and EMG signal data. The script low-pass filters the GRF signals (fourth-order Butterworth, 20 Hz cut-off) and demeans, band-pass filters (20-450 Hz), and full-wave rectifies the EMG signals. The algorithm relies on the stance phase timing provided by the force platform 204 mounted under the right belt of the treadmill 202. Accordingly, the script extracts the data from each right leg stance phase in real-time, based on a 20 N vertical GRF threshold. At the instant of each toe-off, the real-time algorithm calculates and stores: 1) the propulsive peak of the anterior-posterior GRF and 2) the mean push-off MG activity (i.e., that over the second half of stance) as show by 225 in FIG. 3. Although the algorithm uses MG activity based on the fact that the gastrocnemius muscle is considerably involved in forward propulsion, it is also contemplated that EMG data from both the MG and SOL due to their combined contribution to generating ankle power during push-off may be utilized.

Finally, a computer device 250 positioned in front of the treadmill 202 displays points each corresponding to a n-stride average of those measurements (i.e., one dot appears every n strides, scrolling from right to left). Here, “n” represents an integer that can be varied according to the needs of the application. To preserve the ordinate scaling across condition on the user interface of the computer device 250, the algorithm considers the magnitude, variability, and target percent increases of each measure. Therefore, the scaling of each subject's feedback data on the user interface can be normalized by setting the ordinate range from the minimum value during normal walking to the largest target plus half the range observed during normal walking.

Three different approaches to increase propulsion in old adults are contemplated: force feedback, EMG feedback, and auditory stride frequency cueing.

In one embodiment of the invention performed, referred to as “Normal 1 trial”, subjects walk normally for five minutes at 1.25 m/s on the treadmill 202 to allow their movement patterns to stabilize. GRF of old and young subjects is collected and EMG data of old subjects are collected during the final 30 seconds of the 5 minute trial. Young subjects walking normally are tested only to provide reference GRF values. For older subjects, the data from Normal 1 trial is used to calculate targets for the first pair of visual feedback trials—force or EMG, depending on a randomized trial order. Prior to starting the visual feedback trials, the gait cycle is described to each subject in which the late stance phase is emphasized. The late stance phase occurs during which the ankle extends and the muscles of the leg generate a propulsive force on the ground. Each subject is further instructed to more vigorously extend their ankles and push their legs backwards during late stance without excessively vaulting themselves vertically.

For each visual feedback trial, the subjects are asked to match a target line set to 20% and 40% greater than their normal walking for two minutes denoted by: force—F20 and F40 or EMG—EMG20 and EMG40.

To determine whether subjects can maintain a more vigorous push-off after removing visual feedback, the visual feedback is turned off and the subjects are requested to maintain the same exaggerated push-off for one minute. Some subjects can retain a more vigorous push-off for several minutes even after returning to normal walking. After resting for five minutes, the subjects then walk normally on the motorized treadmill for one minute, referred to as “Normal 2 trial”. The Normal 2 trial is used to calculate targets for an alternate pair of visual feedback trials.

In other trials, in order to promote longer steps, the subjects are asked to walk for one minute while matching their steps to the beat of an audio metronome set to step frequencies 10% and 20% slower than normal walking denoted by SF10 and SF20, respectively. The metronome is subsequently turned off and the subjects asked to maintain that same step frequency for one minute.

An algorithm, such as a custom script, analyzes the data and calculates stride-averaged values over the final minute of each normal walking trial, the second minute of each visual feedback trial, and the final 30 seconds of each auditory cueing trial. Starting with the first stride after the visual feedback or auditory cueing is removed, stride-by-stride values of peak propulsive force are calculated, along with push-off MG activity, and stride time during the final minute of the F20/F40, EMG20/EMG40, and SF10/SF20 trials, respectively. Average values are reported for each stride up to the fewest number of strides taken by a subject during this minute, which is approximately 40 strides.

After the data are collected, the individual limbs method (ILM) is used to calculate the instantaneous rates of mechanical work performed by the legs for each condition from the stride-averaged GRF data. The first calculation is the velocity of the body's center of mass (CoM) by integrating the GRF with respect to time. The next calculation is the mechanical work rates over an average stride as the dot product of the three-dimensional right leg GRF and CoM velocity.

Evaluating the distribution of all measurements using a Shapiro-Wilk's test, all outcome measures are normally distributed except for mean push-off MG activity during trials with visual EMG feedback (P<0.01 for EMG20 and EMG 40). The primary outcome measures (peak propulsive GRF and mean push-off MG activity) do not differ between the Normal 1 trial and the Normal 2 trial (P=0.109 and P=0.083, respectively). Because subjects complete the Normal 2 trail after their first round of visual feedback, the Normal 1 trial is used as the baseline condition for all comparisons to avoid any possible confounding factors. It is also confirmed that subjects respond to force and EMG feedback symmetrically.

FIG. 4 is a graph 300 illustrating mean peak propulsive force. As shown in FIG. 4, the graph 300 includes bars 302, 304, 306, 308. Bar 302 illustrates old subjects walking normally. Bar 304 illustrates peak propulsive GRF when the subject is provided with visual force feedback. Bar 306 illustrates peak propulsive GRF when the subject is provided with EMG feedback, and bar 308 illustrates peak propulsive GRF when the subject is provided with stride frequency cueing. FIG. 4 also illustrates the peak propulsive force of younger subjects walking normally.

FIG. 5 is a graph 350 illustrating push-off muscle activity. As shown in FIG. 5, the graph 350 includes bars 352, 354, 356, 358. As shown in FIG. 5, bar 352 illustrates old subjects walking normally. Bar 354 illustrates push-off muscle activity when the subject is provided with visual force feedback. Bar 356 illustrates push-off muscle activity when the subject is provided with EMG feedback, and bar 358 illustrates push-off muscle activity when the subject is provided with stride frequency cueing.

As can be seen in FIG. 4, old subjects walking normally exerted 12.5% smaller peak propulsive GRFs than young adults (P<0.01). However, when provided with real-time propulsive feedback, old subjects significantly increased their propulsive GRFs 304 (FIG. 4) and push-off muscle activities 354 (FIG. 5). Force feedback elicited propulsive GRFs that are either equal to or 10.5% greater than those of young adults walking normally (F20, P=0.87; F40, P=0.02). Those conditions also elicited significant increases in push-off muscle activity (FIG. 5). With EMG feedback, old subjects significantly increased their push-off muscle activities but without increasing their propulsive GRFs (FIG. 5). Force feedback also elicited greater mechanical power generation to propel the body's CoM forward during the push-off phase of walking and to raise the CoM vertically during single support.

FIG. 6 illustrates the mean stance phase ground reaction force (GRF) profiles for old subjects walking with visual force and EMG feedback and auditory stride frequency cueing. FIG. 7 illustrates the mean stance phase gastrocnemius and soleus activity, or EMG profiles for old subjects walking with visual force and EMG feedback and auditory stride frequency cueing. FIG. 8 is a graph illustrating post-feedback retention. Specifically, FIG. 8 shows mean stride-by-stride values of peak propulsive force, push-off gastrocnemius activity, and stride time during the minute after the feedback—visual or auditory cueing—is removed. The horizontal dashed lines in FIG. 8 indicate target percent increase. The results for force feedback, EMG feedback, and stride frequency cueing are shown in FIG. 6, FIG. 7, and FIG. 8 for trials directed to the subject matching a target line set to 20% and 40% greater than its normal walking for two minutes denoted by: force—F20 and F40 and EMG—EMG20 and EMG40, in addition to the subject matching its steps to the beat of an audio metronome set to step frequencies 10% and 20% slower than normal walking denoted by SF10 and SF20.

Likely because both muscles are involved in forward propulsion, feedback of gastrocnemius activity elicited similar increases in soleus muscle activity during push-off (FIG. 7). Old adults generally increased their propulsive function with force and EMG feedback but they did not quite reach the 20% and 40% targets. On average, old subjects increased their propulsive GRF by 15% and 26% for F20 and F40 and their push-off MG activity by 19% and 30% for EMG20 and EMG40, respectively. Moreover, subjects can maintain this more vigorous push-off for at least 40 strides after force feedback is removed (FIG. 8A) or EMG (FIG. 8B) feedback. Only for F40 did subjects show a significant decrease in stride-by-stride propulsive forces after visual feedback is removed (P=0.03).

Auditory stride frequency cueing elicited smaller increases in propulsive GRFs and push-off muscle activities in old adults than walking with feedback of those measures directly (FIG. 4, FIG. 5). Old subjects walked with 8% (P<0.01) and 23% (P<0.01) slower, longer steps than normal for SF10 and SF20, respectively. Similarly, step times are 6% (P=0.01) and 15% (P<0.01) slower than normal for F20 and F40, respectively.

The invention supports that old subjects with propulsive deficits (compared to young subjects) actually have a considerable and underutilized propulsive reserve available during level walking. Further, real-time visual feedback of propulsive effort can effectively call upon this reserve. The subjects are able to significantly and dramatically increase their peak propulsive GRFs and ankle extensor muscle activities when provided with real-time force and EMG feedback compared to normal walking. Moreover, real-time force feedback in old subjects elicited peak propulsive GRFs that were equal to and even greater than those of young subjects. Thus, old subjects with propulsive deficits are not explicitly limited in their capacity to increase forward propulsion during level walking. To the contrary, the subjects have a reserve of at least 26% for exerting greater propulsive GRFs and 49% for increasing ankle extensor muscle recruitment. Remarkably, when provided with feedback, healthy and active old subjects can walk with as vigorous a push-off as young subjects, but do not naturally do so.

Determining whether force or EMG feedback is more effective at improving the forward propulsion of old subjects, it is noted that the target 20% and 40% increases for propulsive force do not correspond to equal increases in push-off EMG. Force feedback requires a considerably more vigorous push-off than the same target percent increase in gastrocnemius activity using EMG feedback. Not surprisingly, asking subjects to push-off more vigorously by increasing MG activity also elicited similar increases in SOL activity. However, while EMG feedback did elicit significantly greater push-off muscle activities in old subjects, not even the 40% target increase in EMG elicited a significant increase in peak propulsive forces or mechanical power generation. Although the real-time propulsive force feedback may more directly and effectively encourage old subjects to utilize their propulsive reserve, both real-time EMG feedback and real-time stride frequency cueing are also valuable.

The invention attempts to use real-time feedback to encourage old subjects to increase their forward propulsion during walking. Old subjects can maintain a more vigorous push-off for at least 40 strides after visual feedback is removed. Although the old subject subjects may have consumed oxygen at a faster rate while walking in the novel way elicited by propulsive feedback compared to walking normally, the characteristic propulsive mechanics of old subjects may explain why they consume ˜20% more metabolic energy than young subjects walking normally. Thus, propulsive feedback training may both improve forward propulsion in old subjects and reduce their metabolic cost.

Finally, sarcopenia and leg muscle weakness may more explicitly limit propulsive GRFs and ankle power generation in sedentary and/or frail old subjects. While resistance training in old subjects can improve their muscle strength and mitigate sarcopenia, strengthening alone generally fails to improve their walking ability. Thus, frail and/or sedentary old subjects may benefit most from leg muscle strengthening to increase their propulsive capacity combined with propulsive feedback training to encourage neural utilization of that capacity.

FIG. 9 illustrates an exemplary computer device 150 that may be used to implement the methods according to the invention. One or more computer devices 150 may carry out the methods presented herein as computer code.

Computer device 150 includes a user interface 152 connected to communication infrastructure 153—such as a bus—, which forwards data such as graphics, text, and information, from the communication infrastructure 153 or from a frame buffer (not shown) to other components of the computer device 150. The user interface 152 may be, for example, a keyboard, touch screen, joystick, trackball, mouse, monitor, speaker, printer, wearable visual user interface such as Google Glass™, any other computer peripheral device, or any combination thereof, capable of entering and/or viewing data.

Computer device 152 includes one or more processors 154, which may be a special purpose or a general-purpose digital signal processor that processes certain information. Computer device 150 also includes a main memory 155, for example random access memory (RAM), read-only memory (ROM), mass storage device, or any combination thereof. Computer device 150 may also include a secondary memory 156 such as a hard disk unit 157, a removable storage unit 158, or any combination thereof. Computer device 150 may also include a communication interface 159, for example, a modem, a network interface (such as an Ethernet card or Ethernet cable), a communication port, a PCMCIA slot and card, wired or wireless systems (such as Wi-Fi, Bluetooth, Infrared), local area networks, wide area networks, intranets, etc.

It is contemplated that the main memory 155, secondary memory 156, communication interface 159, or a combination thereof, function as a computer usable storage medium, otherwise referred to as a computer readable storage medium, to store and/or access computer software including computer instructions. For example, computer programs or other instructions may be loaded into the computer device 150 such as through a removable storage device, for example, a ZIP disk, magnetic tape, portable flash drive, optical disk such as a CD or DVD or Blu-ray, Micro-Electro-Mechanical Systems (MEMS), nanotechnological apparatus. Specifically, computer software including computer instructions may be transferred from the removable storage unit 158 or hard disc unit 157 to the secondary memory 156 or through the communication infrastructure 153 to the main memory 155 of the computer device 150.

Communication interface 159 allows software, instructions and data to be transferred between the computer device 150 and external devices or external networks. Software, instructions, and/or data transferred by the communication interface 159 are typically in the form of signals that may be electronic, electromagnetic, optical or other signals capable of being sent and received by the communication interface 159. Signals may be sent and received using wire or cable, fiber optics, a phone line, a cellular phone link, a Radio Frequency (RF) link, wireless link, or other communication channels.

Computer programs, when executed, enable the computer device 150, particularly the processor 154, to implement the methods of the invention according to computer software including instructions.

The computer device 150 described herein may perform any one of, or any combination of, the steps of any of the methods presented herein. It is also contemplated that the methods according to the invention may be performed automatically, or may be invoked by some form of manual intervention.

The computer device 150 of FIG. 9 is provided only for purposes of illustration, such that the invention is not limited to this specific embodiment. It is appreciated that a person skilled in the relevant art knows how to program and implement the invention using any computer device.

The computer device 150 may be a handheld device and include any small-sized computer device including, for example, a personal digital assistant (PDA), smart hand-held computing device, cellular telephone, or a laptop or netbook computer, hand held console or MP3 player, tablet, or similar hand held computer device, such as an iPad®, iPad Touch® or iPhone®.

FIG. 10 illustrates an exemplary cloud computing system 300 that may be used to implement the methods according to the invention. The cloud computing system 300 includes a plurality of interconnected computing environments. The cloud computing system 300 utilizes the resources from various networks as a collective virtual computer, where the services and applications can run independently from a particular computer or server configuration making hardware less important.

Specifically, the cloud computing system 300 includes at least one client computer 302. The client computer 302 may be any device through the use of which a distributed computing environment may be accessed to perform the methods disclosed herein, for example, a traditional computer, portable computer, mobile phone, personal digital assistant, tablet to name a few. The client computer 302 includes memory such as random access memory (RAM), read-only memory (ROM), mass storage device, or any combination thereof. The memory functions as a computer usable storage medium, otherwise referred to as a computer readable storage medium, to store and/or access computer software and/or instructions.

The client computer 302 also includes a communications interface, for example, a modem, a network interface (such as an Ethernet card), a communications port, a PCMCIA slot and card, wired or wireless systems, etc. The communications interface allows communication through transferred signals between the client computer 302 and external devices including networks such as the Internet 304 and cloud data center 306. Communication may be implemented using wireless or wired capability such as cable, fiber optics, a phone line, a cellular phone link, radio waves or other communication channels.

The client computer 302 establishes communication with the Internet 304—specifically to one or more servers—to, in turn, establish communication with one or more cloud data centers 306. A cloud data center 306 includes one or more networks 310 a, 310 b, 310 c managed through a cloud management system 308. Each network 310 a, 310 b, 310 c includes resource servers 312 a, 312 b, 312 c, respectively. Servers 312 a, 312 b, 312 c permit access to a collection of computing resources and components that can be invoked to instantiate a virtual machine, process, or other resource for a limited or defined duration. For example, one group of resource servers can host and serve an operating system or components thereof to deliver and instantiate a virtual machine. Another group of resource servers can accept requests to host computing cycles or processor time, to supply a defined level of processing power for a virtual machine. A further group of resource servers can host and serve applications to load on an instantiation of a virtual machine, such as an email client, a browser application, a messaging application, or other applications or software.

The cloud management system 308 can comprise a dedicated or centralized server and/or other software, hardware, and network tools to communicate with one or more networks 310 a, 310 b, 310 c, such as the Internet or other public or private network, with all sets of resource servers 312 a, 312 b, 312 c. The cloud management system 308 may be configured to query and identify the computing resources and components managed by the set of resource servers 312 a, 312 b, 312 c needed and available for use in the cloud data center 306. Specifically, the cloud management system 308 may be configured to identify the hardware resources and components such as type and amount of processing power, type and amount of memory, type and amount of storage, type and amount of network bandwidth and the like, of the set of resource servers 312 a, 312 b, 312 c needed and available for use in the cloud data center 306. Likewise, the cloud management system 308 can be configured to identify the software resources and components, such as type of Operating System (OS), application programs, and the like, of the set of resource servers 312 a, 312 b, 312 c needed and available for use in the cloud data center 306.

The invention is also directed to computer products, otherwise referred to as computer program products, to provide software to the cloud computing system 300. Computer products store software on any computer useable medium, known now or in the future. Such software, when executed, may implement the methods according to certain embodiments of the invention. Examples of computer useable mediums include, but are not limited to, primary storage devices (e.g., any type of random access memory), secondary storage devices (e.g., hard drives, floppy disks, CD ROMS, ZIP disks, tapes, magnetic storage devices, optical storage devices, Micro-Electro-Mechanical Systems (MEMS), nanotechnological storage device, etc.), and communication mediums (e.g., wired and wireless communications networks, local area networks, wide area networks, intranets, etc.). It is to be appreciated that the embodiments described herein may be implemented using software, hardware, firmware, or combinations thereof.

The cloud computing system 300 of FIG. 10 is provided only for purposes of illustration and does not limit the invention to this specific embodiment. It is appreciated that a person skilled in the relevant art knows how to program and implement the invention using any computer device or network architecture.

While the disclosure is susceptible to various modifications and alternative forms, specific exemplary embodiments of the invention have been shown by way of example in the drawings and have been described in detail. It should be understood, however, that there is no intent to limit the disclosure to the particular embodiments disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure as defined by the appended claims. 

1. A propulsion system for measuring propulsive force and providing feedback real-time to improve ambulation of a subject, comprising: an ambulation device that facilitates the subject walking, the ambulation device further comprising a force detection device that measures ground reaction force data as the subject walks on the ambulation device and an activity detection device that measures electromyographic signal data from one or more muscles as the subject walks on the ambulation device; and a computer device including a processor and a user interface, the processor receives and analyzes real-time the ground reaction force data and the electromyographic signal data to produce a feedback output displayed on the user interface.
 2. The propulsion system according to claim 1 wherein the ambulation device is a motorized treadmill.
 3. The propulsion system according to claim 1 wherein the force detection device is a force platform or force transducers.
 4. The propulsion system according to claim 1 wherein the activity detection device are electrodes with differential amplifiers.
 5. The propulsion system according to claim 1 wherein the one or more muscles are the soleus muscles of the legs.
 6. The propulsion system according to claim 1 wherein the one or more muscles are the gastrocnemius muscles of the legs.
 7. The propulsion system according to claim 1 wherein the feedback output is a graphic illustration or an auditory cue of one or more selected from the group comprising: the ground reaction force data, the electromyographic signal data, and stride frequency.
 8. The propulsion system according to claim 1 wherein the processor analyzes real-time the ground reaction force data to calculate a propulsive peak force or propulsive impulse from an anterior-posterior ground reaction force.
 9. The propulsion system according to claim 1 wherein the processor analyzes real-time the electromyographic signal data to calculate a mean push-off electromyographic signal.
 10. A method for measuring propulsive force and providing feedback real-time to improve ambulation of a subject, comprising the steps of: providing an ambulation device to facilitate the subject walking, using a force detection device to measure ground reaction force data as the subject walks on the ambulation device; utilizing an activity detection device to measure electromyographic signal data from one or more muscles as the subject walks on the ambulation device; analyzing real-time by a processor the ground reaction force data and the electromyographic signal data to produce a feedback output; and communicating the feedback output on a user interface.
 11. The method according to claim 10 wherein the analyzing step further comprises the step of calculating a propulsive peak or a propulsive impulse of an anterior-posterior ground reaction force.
 12. The method according to claim 10 wherein the analyzing step further comprises the step of computing a mean push-off electromyographic signal.
 13. The method according to claim 10 wherein the one or more muscles are the soleus muscles of the legs.
 14. The method according to claim 10 wherein the one or more muscles are the gastrocnemius muscles of the legs.
 15. The method according to claim 10 wherein the communicating step further comprises the step of displaying a graphic illustration of one or more selected from the group comprising: the ground reaction force data, the electromyographic signal data, and a stride frequency.
 16. The method according to claim 10 wherein the communicating step further comprises the step of sounding an auditory cue of one or more selected from the group comprising: the ground reaction force data, the electromyographic signal data, and a stride frequency. 